Text embedder
Defines an Azure AI text embedder.
Example
This flow processes a user's chat question by first receiving it through a Chat completion trigger, then converting it into an embedding vector using a text embedder, and performs a Vector search in a postgreSQL database for relevant context. The result from the vector search, along with the user input, is then passed to the Chat completion, which generates the response which is returned to the client via the Return node.
Properties
Name | Type | Description |
---|---|---|
Title | Optional | The title of the action. |
Connection | Required | Defines the connection to an Azure AI Foundry resource. |
Model | Required | Specifies the model deployment name, which corresponds to the Name (not the model id) of the deployed model in Azure AI Foundry. In the Azure Portal, the deployment name can be found under Resource Management > Model Deployments. |
Dimensions | Optional | Specifies the number of dimensions to be used. |
Result variable name | Required | Defines the variable name in which the result will be stored. TextEmbedder ![]() |
Description | Optional | A field to add additional details or notes about the action. |
Returns
Returns the AzureAITextEmbedder
instance generated by this action.